The Pio Insights reports live outside the Pio App. The numbers are updated monthly, and shared by email. This article will give you an overview of the numbers presented in the reports.
Picking Performance
This report shows picking volume and picking performance for the selected period (usually per month).
Picking Volume lists how many
- bin presentations - total number of bins picked from
- order lines - total number of order lines picked this period
- orders - total number of orders for all order lines picked
- order lines per hour - average order lines per order
Picking Performance lists how many
- bin presentations per hour - average performance of picking
- order lines per hour - average number of order lines picked per hour
- active hours picking - total hours the Port has been in picking flow
- seconds per order - average number of seconds spent picking per order
This report can also give the details on the picking performance from grid vs. from shelves.
Note: The report has filtered out sessions where Port has been left open and not used for a longer period of time.
Storing Performance
The report is split between Storing Volume and Storing Performance for the selected period.
Storing Volume lists how many
- items stored - total for storing both in the grid and on shelves
- bin presentations - the total number of bins used for storing all the products
- SKUs - total number of SKUs added to the grid or on shelves
- items per compartment - average number of items stored in each bin
Storing Performance lists how many
- bin presentations per hour - average number of bins presented for storing
- SKUs per hour - average number of SKUs stored
- active hours storing - total hours the Port has been in Storing flow
Search Performance
The Search Performance is meant to give an update on how many products, bins and kits have been searched up and manually added or removed inventory.
Search Volume lists how many
- items added - how many products are added by searching bin/SKU/kit
- items removed - how many products are removed by searching bin/SKU/kit
- bin presentations - how many bins have been presented by search
- SKUs - how many product SKUs have been searched
Search Performance lists how many
- bin presentations per hour - average number of bins presented per hour
- SKUs per hour - average number of SKUs presented per hour
- active hours - total hours the Port has been in Search flow
Users Leaderboard
The users leaderboard lists all the active users in Pio in the given period, and shows , how many hours they have been picking and how long time spent packing the orders.
Users lists include the following details
- order lines/h - average number of order lines picked per hour
- hours picking -total number of hours the user has spent in picking flow
- order lines - total number of orders picked
- packing time (per order) - seconds spent packing
- OL / order - average number of order lines per order
Grid Fill rate
Grid Fill rate report is an advanced calculation of the fill rate of your Pio grid. The Total fill rate percentage is a combination of how many compartments and bins are in use, and the average fill rate of the bins and compartments.
Average fill rate
The average fill rate is a calculated/theoretical percentage of how well the compartments of the bins are filled. Max number of a SKU stored in a compartment (historically) is used as a base here.
Example: If you have once filled a compartment of a 2-split bin with 20x of a specific SKU (ex. t-shirts), then 20 is used as max capacity (100%) for this product type in a 2-split compartment.
After picking from this compartment several times, you have fewer products left, and the fill rate gets lower. Leaving 10 t-shirts in the same 2-split compartment, will give a 50% fill rate for this product.
If the same SKU is stored in multiple bins, the average fill rate will be calculated based on fill rate for each of the compartments where it is stored.
Total fill rate
The total fill rate is a combination of the average fill rate and the number of bins/compartments in use.
A way to optimize the total fill rate would be to raise the average fill rate and reduce the percentage of compartments and bins used.
Layout definitions
When listing the different bin layouts, we use a code to reflect how the bin dividers are inserted. Here is a list of what they represent:
11 = 1x1 compartment (full bin, no dividers)
21 = 2x1 compartments, 2-split
22 = 2x2 compartments, 4-split
41 = 4x1 compartments, 4-split
42 = 4x2 compartments, 8-split
44 = 4x4 compartments, 16-split
Content - SKU
Content overview per SKU is a complete list of all items in stock (Pio grid + shelves). This report is shared as an excel-file where you can filter and sort the products and use it the way you need.
Summarized data
- items in stock - number of items in stock when report was generated
- SKUs - total number of SKUs in Pio
- annualized turnover - used for inventory turnover; how many items you have in stock vs how many is sold. A higher ratio tends to point to strong sales and a lower one to weak sales
- items per bin - average number of items per bins
- fill rate - filter for how the fill rate of bins can affect the turnover of inventory
Specification of data in excel sheet
- webshop - specification of online store
- product name - name of SKU
- # of bins - how many bins the SKU is stored in
- # of compartments - how many compartments the SKU is stored in
- items per bin - average number of products stored in a bin
- avg fill rate - average fill rate of all compartments where the SKU is stored
- max fill rate - highest fill rate for any of the compartments where the SKU is stored
- min fill rate - lowest fill rate for any of the compartments where the SKU is stored
- annualized turnover - how many you have in stock vs how many sold. Ex. 100 items of a SKU in stock, 6 items sold the last month, the annualized turnover will be 0,06
- days to empty - how many days until the SKU is sold out
- items in stock - start - number of items in stock when period started
- picked - how many items picked in the period
- inspected in - how many items added to stock manually by Search flow
- stored - how many items added to stock by Storing flow
- items in stock - end - how many items in stock when period ended
- avg days in stock - how many days a SKU has been in Pio storage. If the same SKU is stored in multiple bins, then 'Avg Days in Stock' is the average of all the bins it is stored in
The Content SKU report is a detailed view of the stock you have in the grid. It can be used for both forecasting and to plan for clean & merge products in bins.
Content - Compartment
Content overview per compartment is a complete list of all inventory and how it is stored in the different compartments of bins.
Summarized data
- items in stock - number of items in stock when report was generated
- SKUs - total number of SKUs in Pio
- annualized turnover - used for inventory turnover; how many items you have in stock vs how many is sold. A higher ratio tends to point to strong sales and a lower one to weak sales
- items per bin - average number of items per bins
Specification of data in excel sheet
- location - where the product is stored in Pio (grid or shelf)
- bin ID - specification of bin where the product is stored
- comp. ID - specification of which compartment in a bin where the product is stored
- SKU - product SKU (Stock Keeping Unit)
- webshop - name of the online store the product belongs to
- product name - name of the product
- items in stock - total number of products in this specific bin
- max per bin - the maximum number of items of this SKU that have been stored in a bin
- split - the layout of the bin
- max per compartment - the maximum number of items of this SKU that have been stored in one compartment
- fill rate - calculated fill rate based on the max item per compartment/bin and items in this specific compartment/bin
- created at year/month/date - the time of storing in this specific compartment
- days in stock - how many days the product has been stored in this specific compartment
A combination of data in both of the Content-reports will give the opportunity to filter out products that have a low turnover and how long it will take to empty the stock, SKUs that are stored in many bins, bins with a low fill rate, SKUs that haven't been picked or stored the previous month, and much more.